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The fully-automatic Sentinel-1 Global Flood Monitoring service: Scientific challenges and future directions
Get PDFSentinel-1 is a unique resource for global flood monitoring, providing systematic, weather-independent Synthetic Aperture Radar (SAR) imagery with unprecedented coverage. To overcome limitations of on-demand flood mapping services that depend on human operators to collect and interpret satellite images, a fundamentally new approach was adopted by the Global Flood Monitoring (GFM) service. This service, which was launched in 2021 as part of the Copernicus Emergency Management Service (CEMS), processes all Sentinel-1 land images acquired in VV polarisation fully automatically in near-real time. This article presents the first comprehensive analysis of GFM’s scientific achievements and challenges during its initial years of operation. To map floods reliably under diverse environmental conditions, GFM combines three complementary flood-mapping algorithms with reference water datasets to differentiate flooded areas from permanent and seasonal water bodies. The service also offers a novel flood-likelihood layer and contextual information to highlight areas where flood mapping is unreliable or not feasible. These data layers were derived from a global 20 m backscatter datacube containing approximately 379 billion land surface pixels. This datacube also made it possible to generate the first global Sentinel-1 flood archive (2015 to present). Our performance analysis shows that GFM typically delivers flood maps within five hours of image acquisition. However, a significant percentage of floods may go undetected due to coverage gaps. Initial evaluation results show that good accuracies are achieved for larger-scale floods and regions in the temperate and tropical zones, while accuracies are lower for smaller-scale floods and arid environments. The GFM service will continue to improve service quality by enhancing flood detection capabilities using improved algorithms and additional data, such as the VH channel from Sentinel-1 or L-band data from the upcoming ROSE-L mission
Sustainable phosphate-catalyzed synthesis of non-symmetric pyrazines in water – mechanistic insights, biocatalytic applications and industrial potential
No full textPyrazines are pivotal flavor compounds with widespread applications in the food, pharmaceutical, and chemical industries. Their natural abundance is low, and traditional synthetic methods often involve hazardous conditions unsuitable for the food sector. In this study, we present a novel biocatalytic methodology for synthesising non-symmetric trisubstituted pyrazines using aminoacetone dimerisation followed by electrophile incorporation under environmentally benign conditions, catalyzed by phosphate anion. The approach includes the employment of l-threonine dehydrogenase from Cupriavidus necator to generate aminoacetone in situ from natural l-threonine, integrating biocatalysis with green chemistry principles. Detailed mechanistic investigations, supported by control experiments and DFT calculations, revealed the critical role of phosphate buffering, an E1cB elimination, and a tautomerisation-driven pathway for product formation. The methodology demonstrates broad substrate scope and scalability, yielding pyrazines with diverse structural modifications up to 96% yields. This work establishes a starting point for the industrial production of non-symmetric pyrazines, addressing current regulatory and environmental demands in the flavor and fragrance sector
A Unified Framework for Pattern Recovery in Penalized and Thresholded Estimation and its Geometry
No full textWe consider the framework of penalized estimation where the penalty term is given by a real-valued polyhedral gauge, which encompasses methods such as LASSO, generalized LASSO, SLOPE, OSCAR, PACS and others. Each of these estimators is defined through an optimization problem and can uncover a different structure or “pattern” of the unknown parameter vector. We define a novel and general notion of patterns based on subdifferentials and formalize an approach to measure pattern complexity. For pattern recovery, we provide a minimal condition for a particular pattern to be detected by the procedure with positive probability, the so-called accessibility condition. Using our approach, we also introduce the stronger noiseless recovery condition. For the LASSO, it is well known that the irrepresentability condition is necessary for pattern recovery with probability larger than 1/2 and we show that the noiseless recovery plays exactly the same role in our general framework, thereby unifying and extending the irrepresentability condition to a broad class of penalized estimators. We also show that the noiseless recovery condition can be relaxed when turning to so-called thresholded penalized estimators: we prove that the necessary condition of accessibility is already sufficient for sure pattern recovery by thresholded penalized estimation provided that the noise is small enough. Throughout the article, we demonstrate how our findings can be interpreted through a geometrical lens
Development and EMG/metabolic assessment of a passive shoulder exoskeleton providing adjustable support for high arm elevation
No full textExoskeletons are increasingly used to reduce physical strain during overhead and repetitive manual tasks. This study evaluated a novel passive upper limb exoskeleton adjustable for maximum support at different arm elevation angles. Ten male participants performed repetitive arm movements with a 2.5 kg weight along a sinusoidal trajectory at elevations between 90° and 135° in the sagittal plane. Use of the exoskeleton resulted in a statistically significant (p 0.05). With exoskeleton use, reductions were observed in heart rate, [Formula: see text] , [Formula: see text] and RER, although only changes in [Formula: see text] and RER were statistically significant. Respiratory frequency did not decrease (p > 0.05). Future research should include a more diverse participant group, tasks that better represent real-world manual labour, and direct comparisons with already established exoskeletons
Identifying Electronic Doorway States in the Secondary Electron Emission from Layered Materials
No full textUntersuchungen eines Profil-Laserscanners für den Einsatz bei geodätischen Deformationsmessungen
No full textHERMES: an open-source mining tool for open-access literature
No full textMotivation: The exponential growth of open-access scientific literature presents researchers with unprecedented opportunities but also poses a significant challenge: how to efficiently identify and prioritize relevant publications in a transparent and customizable manner. Existing search engines index large volumes of biomedical literature but rarely provide user-defined ranking options, reproducibility, or integration of domain-specific criteria. This gap is particularly limiting for specialized fields, where nuanced keyword combinations, literature recency, and contextual interpretation are critical.
Results: We present HERMES, an open-source literature mining tool for targeted retrieval and ranking of full-text open-access publications from PubMed Central (PMC). HERMES employs a composite scoring algorithm that integrates keyword frequency, citation counts, and publication age to prioritize publications. It further supports summarization, biomedical entity recognition, and PDF report generation. An intuitive graphical user interface (GUI) allows researchers without programming expertise to perform complex literature mining tasks, while multithreaded processing ensures efficiency for large-scale queries. HERMES provides a reproducible and adaptable framework for literature discovery, empowering researchers to rapidly identify relevant literature and promoting transparency and community-driven extension.
Availability and implementation: HERMES (version 1.2) is implemented in Python (3.11). The source code is freely available on GitHub at https://github.com/julien-charest/hermes and is distributed under the GPL-3 license
Sicherheitstests für das Bluetooth Low Energy Protokoll mit Kombinatorischen Methoden
Get PDFDer Bluetooth Low Energy (BLE) Standard ist eine weit verbreitete drahtlose Kommunikationstechnologie für Geräte des Internets der Dinge (IoT) und ermöglicht energiesparende Datenübertragung für verschiedene Anwendungen. Da die Verbreitung von BLE rasant zunimmt, wird die Gewährleistung der Sicherheit zum Schutz vor potenziellen Schwachstellen immer wichtiger. Anbieter BLE fähiger Mikrocontroller müssen BLE Protokolle in ihren Geräten entsprechend der Bluetooth Core Specification implementieren. Trotz der Standardisierungsbemühungen wurden in den BLE Implementierungen verschiedener Anbieter mithilfe manueller und automatisierter Methoden Schwachstellen entdeckt, die potentiell Millionen von Geräten betreffen. Dies ist teilweise auf die Komplexität der Protokolle zurückzuführen, die sich aus der überwältigenden Anzahl möglicher Konfigurationen ergibt und darauf, dass ein gründliches Testen der Implementierung aufgrund der Host-Controller-Schnittstelle (HCI) schwierig ist. In den letzten Jahren wurde das GreyHound Fuzzing Framework entwickelt, das mithilfe kostengünstiger Hardware beliebige BLE Pakete bis zur Linklayer Schicht senden kann. Da Fuzzing von Natur aus probabilistisch ist, ersetzen wir die oben genannte Fuzzing Methode durch einen kombinatorischen Sicherheits Test (CST) Ansatz, der eine garantierte Abdeckung des modellierten Eingabebereichs bietet. Durch die Generierung von Testfällen, die mehrere Kombinationen von Eingabeparametern abdecken, wollen wir Schwachstellen identifizieren, die mit herkömmlichen Testmethoden möglicherweise nicht entdeckt werden. Wir evaluieren unseren Ansatz anhand von Tests mit zehn verschiedenen BLE-Geräten mit unterschiedlichen Firmware Versionen. Insgesamt identifizieren wir 19 verschiedene Probleme, reproduzieren Ergebnisse früherer Arbeiten und decken zusätzliche Fehler auf. Um die Wirksamkeit unserer Methode zu überprüfen, vergleichen wir zusätzlich die Leistung unseres CST-Tools mit der des ursprünglichen Fuzzers und vergleichen deren Ausführungszeit und Fehlererkennungsfähigkeiten.The Bluetooth Low Energy (BLE) standard is a widely used wireless communication technology for Internet of Things (IoT) devices, enabling low-power data transmission for various applications. As the adoption of BLE continues to grow rapidly, ensuring their security becomes more and more important to protect against potential vulnerabilities. Vendors of BLE capable micro controllers are required to implement BLE protocols in their manufactured devices compliant to the Bluetooth Core Specification. Despite the efforts of standardization, several vulnerabilities were discovered in the BLE protocol implementations of multiple vendors using manual and automated methods, potentially affecting millions of devices. This can partially be attributed to the protocol's complexity, stemming from an overwhelming number of possible configurations and the fact that it is difficult to test implementations thoroughly due to the Host Controller Interface (HCI). In recent years, the GreyHound fuzzing framework was developed, which is able to send arbitrary BLE packets down to the link layer, using inexpensive consumer hardware. Since fuzzing is inherently probabilistic, we replace the aforementioned fuzzing method with a Combinatorial Security Testing (CST) approach that provides a guaranteed degree of input space coverage over the parameter model. By generating test cases that cover multiple combinations of input parameters, we aim to identify vulnerabilities that may not be uncovered through traditional testing methods. We evaluate our approach by testing 10 different BLE devices with a variety of firmware versions. In total we identify 19 distinct issues, replicating findings of the previous work and uncovering additional faults. To examine the effectiveness of our method, we additionally provide a performance comparison of our CST tool against the original fuzzer, contrasting their execution time and fault detection capabilities